Thesis (M.Com.(Agriculture))--University of Pretoria, 2007. / Summary in English. Includes bibliographical references.

published_or_final_version / Mathematics / Master / Master of Philosophy

Not available

This thesis challenges the idea that buyer-supplier relations can be objectively 'managed' in all cases by firms in the same 'supply chain'. The study examines this argument in relation to a small network of buyer and supplier finns in one industry, ceramic tableware production. The first significant gap found in the 'supply chain management' literature was that the focus of research failed to examine in significant detail the intricacies of why organizations are often forced to 'react' to changes in inter-finn relations, rather than being able to 'manage' such events. A second gap in existing research was its bias toward researching a limited set of industries such as automotives and food production, where manufacturers or assemblers often hold pivotal roles in the supply chain. A final gap in supply chain research was the weak linkage between supply chain management and wider debates relating to productive and organizational change. In addition, the area of literature encapsulating discussions relating to the industrial agglomeration of finns within the 'industrial district' has been used in the past to chart shifting structures for buyer-supplier and infrastructural organization. A strong analytical approach is developed in this thesis that shows the 'softer' aspects of supply chain interaction. The research shows that, although it is possible to 'manage' the pattern of interaction in a network from a focal finn perspective, wider inter-personal, dyadic and network activities do present difficulties in this 'management' activity. This leads to the conclusion that 'supply chain management' may not be a clear cut activity which is simple to apply. At the aggregated network level of interaction, piecemeal evidence was found to support claims for any significant shift in buyer-supplier relations or productive organization that is encapsulated in any of the variant fonns of the Marshallian 'industrial district'.

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Organizations have indicated that RFID technology will revolutionise the supply chain in South Africa. There are, however, a number of challenges and issues, including the relatively high costs of the technology and the lack of mature standards, that need to be overcome before this reality is achieved. Research has confirmed that selected organizations understand that there are number of key benefits to be gained from implementing RFID technology. The collaboration between the supply chain partners has been identified as the requirement for the achievement of these benefits. Manufacturers are lagging behind their counterparts, with the research suggesting that they are reluctant to adopt the technology. Retailers and logistics suppliers have been identified as the main beneficiaries of implementing RFID technology. Retailers are expected to follow the American approach with mandates being issued to manufacturers to drive the adoption of RFID technology. RFID technology is to be implemented in the medium-to-long term with none of the respondents currently using the technology. / Thesis (MBA)-University of KwaZulu-Natal, 2005.

The manufacturing strategy literature is reviewed and it is found to centre on content and process models. However, a number of other issues are present in the literature whose relationship to the central process and content models is less clear. These include the trade-off, focus, flexibility, and generic manufacturing strategies. It is noted that the manufacturing strategy literature does not fully address product customisation. The literature relating to the interface between marketing and manufacturing is found to concentrate either on the identification of conflict areas, or on strategic reconciliation between the functions. Writers in this field do give greater emphasis to product customisation. A case-study method is adopted for the research and the design involves four firms in varying industries. The firms manufacture fork-lift trucks, microswitches, telephone switching systems and diaries, respectively. The case-studies comprise quantitative and qualitative data, and each case chapter includes case-specific analysis. The analysis of all the cases finds that customisation has a very important effect on manufacturing performance. The firms have inconsistencies within their manufacturing strategies, but these are found to rest not only on the firms' manufacturing products with different volume requirements in the same plant, but also on the fact of some of the products being custom-designed. The interface between marketing and manufacturing is found to be more complex and variable than the literature would suggest. The role that customised products play in relationships with customers also varies, although this is inconsistently recognised by the firms.Based on the case-data, a model of product customisation is proposed. This incorporates customisation, flexibility, product architecture, the manufacturing strategy trade-off and the competitive criteria.

Decisions on facility location play a vital role in the planning stage of a supply chain because a facility configuration provides a form, and structure for the supply chain, after which activity interaction between among supply chain members can be established. An optimal facility set can provide best operating performance of the supply chain. This research applied a Genetic Algorithm (GA) scheme for modelling a facility location problem for an agricultural supply chain. As a grouping problem, the research aim is to group production nodes into groups and then define group centroids as a facility (e.g. gran storage). Grouping genetic algorithm (GGA) is then specifically introduced to solve the problem because of the special characteristics of GGA in solving a grouping problem. / Thesis (PhDTransportSystemsEngineering)--University of South Australia, 2006.

Thesis (DBA(DoctorateofBusinessAdministration))--University of South Australia, 2005.